This Edureka Data Science course slides will take you through the basics of Data Science - why Data Science, what is Data Science, use cases, BI vs Data Science, Data Science tools and Data Science lifecycle process. This is ideal for beginners to get started with learning data science.
You can read the blog here: https://goo.gl/OoDCxz
You can also take a complete structured training, check out the details here: https://goo.gl/AfxwBc
Data Science Training | Data Science Tutorial | Data Science Certification | ...Edureka!
This Edureka Data Science Training will help you understand what is Data Science and you will learn about different Data Science components and concepts. This tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Data Science concepts. Below are the topics covered in this tutorial:
1. What is Data Science?
2. Job Roles in Data Science
3. Components of Data Science
4. Concepts of Statistics
5. Power of Data Visualization
6. Introduction to Machine Learning using R
7. Supervised & Unsupervised Learning
8. Classification, Clustering & Recommenders
9. Text Mining & Time Series
10. Deep Learning
To take a structured training on Data Science, you can check complete details of our Data Science Certification Training course here: https://goo.gl/OCfxP2
Data Science For Beginners | Who Is A Data Scientist? | Data Science Tutorial...Edureka!
** Data Science Certification using R: https://www.edureka.co/data-science **
This Edureka "Data Science for Beginners" PPT talks about the basic concepts of Data Science, which includes machine learning algorithms as well as the roles & responsibilities of a Data Scientist. It also includes a demo using R Studio, that attempts to make sense of all the Data generated in the real world. This PPT talks about the most crucial aspects of data science and covers the following topics:
Why Data Science?
What is Data Science?
Who is a Data Scientist?
What does a Data Scientist do?
How to solve a problem in Data Science?
Data Science Tools
Demo
Check out our Data Science Tutorial blog series: http://bit.ly/data-science-blogs
Check out our complete YouTube playlist here: http://bit.ly/data-science-playlist
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Data Science Tutorial | Introduction To Data Science | Data Science Training ...Edureka!
This Edureka Data Science tutorial will help you understand in and out of Data Science with examples. This tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Data Science concepts. Below are the topics covered in this tutorial:
1. Why Data Science?
2. What is Data Science?
3. Who is a Data Scientist?
4. How a Problem is Solved in Data Science?
5. Data Science Components
Data Science Tutorial | What is Data Science? | Data Science For Beginners | ...Edureka!
** Data Science Certification using R: https://www.edureka.co/data-science **
In this PPT on Data Science Tutorial, you’ll get an in-depth understanding of Data Science and you’ll also learn how it is used in the real world to solve data-driven problems. It’ll cover the following topics in this session:
Need for Data Science
Walmart Use case
What is Data Science?
Who is a Data Scientist?
Data Science – Skill set
Data Science Job roles
Data Life cycle
Introduction to Machine Learning
K- Means Use case
K- Means Algorithm
Hands-On
Data Science certification
Blog Series: http://bit.ly/data-science-blogs
Data Science Training Playlist: http://bit.ly/data-science-playlist
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Data science is different from Data Analytics,Data Engineering,Big Data.
Presentation about Data Science.
What is Data Science its process future and scope.
Data Science Presentation By Amit Singh.
"Sexiest job of 21st century"
Data Science Training | Data Science Tutorial for Beginners | Data Science wi...Edureka!
***** Data Science Training - https://www.edureka.co/data-science *****
This Edureka tutorial on "Data Science Training" will provide you with a detailed and comprehensive training on Data Science, the real-life use cases and the various paths one can take to become a data scientist. It will also help you understand the various phases of Data Science.
Data Science Blog Series: https://goo.gl/1CKTyN
http://www.edureka.co/data-science
Data Science Training | Data Science Tutorial | Data Science Certification | ...Edureka!
This Edureka Data Science Training will help you understand what is Data Science and you will learn about different Data Science components and concepts. This tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Data Science concepts. Below are the topics covered in this tutorial:
1. What is Data Science?
2. Job Roles in Data Science
3. Components of Data Science
4. Concepts of Statistics
5. Power of Data Visualization
6. Introduction to Machine Learning using R
7. Supervised & Unsupervised Learning
8. Classification, Clustering & Recommenders
9. Text Mining & Time Series
10. Deep Learning
To take a structured training on Data Science, you can check complete details of our Data Science Certification Training course here: https://goo.gl/OCfxP2
Data Science For Beginners | Who Is A Data Scientist? | Data Science Tutorial...Edureka!
** Data Science Certification using R: https://www.edureka.co/data-science **
This Edureka "Data Science for Beginners" PPT talks about the basic concepts of Data Science, which includes machine learning algorithms as well as the roles & responsibilities of a Data Scientist. It also includes a demo using R Studio, that attempts to make sense of all the Data generated in the real world. This PPT talks about the most crucial aspects of data science and covers the following topics:
Why Data Science?
What is Data Science?
Who is a Data Scientist?
What does a Data Scientist do?
How to solve a problem in Data Science?
Data Science Tools
Demo
Check out our Data Science Tutorial blog series: http://bit.ly/data-science-blogs
Check out our complete YouTube playlist here: http://bit.ly/data-science-playlist
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Data Science Tutorial | Introduction To Data Science | Data Science Training ...Edureka!
This Edureka Data Science tutorial will help you understand in and out of Data Science with examples. This tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Data Science concepts. Below are the topics covered in this tutorial:
1. Why Data Science?
2. What is Data Science?
3. Who is a Data Scientist?
4. How a Problem is Solved in Data Science?
5. Data Science Components
Data Science Tutorial | What is Data Science? | Data Science For Beginners | ...Edureka!
** Data Science Certification using R: https://www.edureka.co/data-science **
In this PPT on Data Science Tutorial, you’ll get an in-depth understanding of Data Science and you’ll also learn how it is used in the real world to solve data-driven problems. It’ll cover the following topics in this session:
Need for Data Science
Walmart Use case
What is Data Science?
Who is a Data Scientist?
Data Science – Skill set
Data Science Job roles
Data Life cycle
Introduction to Machine Learning
K- Means Use case
K- Means Algorithm
Hands-On
Data Science certification
Blog Series: http://bit.ly/data-science-blogs
Data Science Training Playlist: http://bit.ly/data-science-playlist
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Data science is different from Data Analytics,Data Engineering,Big Data.
Presentation about Data Science.
What is Data Science its process future and scope.
Data Science Presentation By Amit Singh.
"Sexiest job of 21st century"
Data Science Training | Data Science Tutorial for Beginners | Data Science wi...Edureka!
***** Data Science Training - https://www.edureka.co/data-science *****
This Edureka tutorial on "Data Science Training" will provide you with a detailed and comprehensive training on Data Science, the real-life use cases and the various paths one can take to become a data scientist. It will also help you understand the various phases of Data Science.
Data Science Blog Series: https://goo.gl/1CKTyN
http://www.edureka.co/data-science
YouTube Link: https://youtu.be/aGu0fbkHhek
** Data Science Master Program: https://www.edureka.co/masters-program/data-scientist-certification **
This Edureka PPT on "Data Science Full Course" provides an end to end, detailed and comprehensive knowledge on Data Science. This Data Science PPT will start with basics of Statistics and Probability and then moves to Machine Learning and Finally ends the journey with Deep Learning and AI. For Data-sets and Codes discussed in this PPT, drop a comment.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
What Is Data Science? | Introduction to Data Science | Data Science For Begin...Simplilearn
This Data Science Presentation will help you in understanding what is Data Science, why we need Data Science, prerequisites for learning Data Science, what does a Data Scientist do, Data Science lifecycle with an example and career opportunities in Data Science domain. You will also learn the differences between Data Science and Business intelligence. The role of a data scientist is one of the sexiest jobs of the century. The demand for data scientists is high, and the number of opportunities for certified data scientists is increasing. Every day, companies are looking out for more and more skilled data scientists and studies show that there is expected to be a continued shortfall in qualified candidates to fill the roles. So, let us dive deep into Data Science and understand what is Data Science all about.
This Data Science Presentation will cover the following topics:
1. Need for Data Science?
2. What is Data Science?
3. Data Science vs Business intelligence
4. Prerequisites for learning Data Science
5. What does a Data scientist do?
6. Data Science life cycle with use case
7. Demand for Data scientists
This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course.
Why learn Data Science?
Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. Data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data.
The Data Science with python is recommended for:
1. Analytics professionals who want to work with Python
2. Software professionals looking to get into the field of analytics
3. IT professionals interested in pursuing a career in analytics
4. Graduates looking to build a career in analytics and data science
5. Experienced professionals who would like to harness data science in their fields
Introduction to various data science. From the very beginning of data science idea, to latest designs, changing trends, technologies what make then to the application that are already in real world use as we of now.
In this presentation, I have talked about Big Data and its importance in brief. I have included the very basics of Data Science and its importance in the present day, through a case study. You can also get an idea about who a data scientist is and what all tasks he performs. A few applications of data science have been illustrated in the end.
How to Become a Data Analyst? | Data Analyst Skills | Data Analyst Training |...Edureka!
** Data Analytics Masters' Program: https://www.edureka.co/masters-program/data-analyst-certification **
This Edureka PPT on "How to become a data analyst" will provide you with a crisp knowledge of who a data analyst is and what are the roles and responsibilities of a data analyst. The salary trends and the companies hiring Data Analyst.
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Data Science With Python | Python For Data Science | Python Data Science Cour...Simplilearn
This Data Science with Python presentation will help you understand what is Data Science, basics of Python for data analysis, why learn Python, how to install Python, Python libraries for data analysis, exploratory analysis using Pandas, introduction to series and dataframe, loan prediction problem, data wrangling using Pandas, building a predictive model using Scikit-Learn and implementing logistic regression model using Python. The aim of this video is to provide a comprehensive knowledge to beginners who are new to Python for data analysis. This video provides a comprehensive overview of basic concepts that you need to learn to use Python for data analysis. Now, let us understand how Python is used in Data Science for data analysis.
This Data Science with Python presentation will cover the following topics:
1. What is Data Science?
2. Basics of Python for data analysis
- Why learn Python?
- How to install Python?
3. Python libraries for data analysis
4. Exploratory analysis using Pandas
- Introduction to series and dataframe
- Loan prediction problem
5. Data wrangling using Pandas
6. Building a predictive model using Scikit-learn
- Logistic regression
This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you'll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course.
Why learn Data Science?
Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. Data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data.
You can gain in-depth knowledge of Data Science by taking our Data Science with python certification training course. With Simplilearn Data Science certification training course, you will prepare for a career as a Data Scientist as you master all the concepts and techniques.
Learn more at: https://www.simplilearn.com
The presentation is about the career path in the field of Data Science. Data Science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data.
Data Science Training | Data Science For Beginners | Data Science With Python...Simplilearn
This Data Science presentation will help you understand what is Data Science, who is a Data Scientist, what does a Data Scientist do and also how Python is used for Data Science. Data science is an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining. This Data Science tutorial will help you establish your skills at analytical techniques using Python. With this Data Science video, you’ll learn the essential concepts of Data Science with Python programming and also understand how data acquisition, data preparation, data mining, model building & testing, data visualization is done. This Data Science tutorial is ideal for beginners who aspire to become a Data Scientist.
This Data Science presentation will cover the following topics:
1. What is Data Science?
2. Who is a Data Scientist?
3. What does a Data Scientist do?
This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course.
Why learn Data Science?
Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. A data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data.
You can gain in-depth knowledge of Data Science by taking our Data Science with python certification training course. With Simplilearn’s Data Science certification training course, you will prepare for a career as a Data Scientist as you master all the concepts and techniques. Those who complete the course will be able to:
1. Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics.
Install the required Python environment and other auxiliary tools and libraries
2. Understand the essential concepts of Python programming such as data types, tuples, lists, dicts, basic operators and functions
3. Perform high-level mathematical computing using the NumPy package and its largelibrary of mathematical functions.
Learn more at: https://www.simplilearn.com
This video includes:
Purpose of Data Science, Role of Data Scientist, Skills required for Data Scientist, Job roles for Data Scientist, Applications of Data Science, Career in Data Science.
Data Science is a wonderful technology that has applications in almost every field. Let's learn the basics of this domain on 16th March at (time).
Agenda
1. What is Data Science? How is it different from ML, DL, and AI
2. Why is this skill in demand?
3. What are some popular applications of Data Science
4. Popular tools and frameworks used in Data Science
My presentation at The Richmond Data Science Community (Jan 2018). The slides are slightly different than what I had presented last year at The Data Intelligence Conference.
This Angular 4 tutorial will introduce you to angular 4 components.
To watch the YouTube videos in this Angular 4 tutorial playlist, click here: https://www.youtube.com/watch?v=R4wGCHzn6-Q&list=PL9ooVrP1hQOF4aDuqaWYWSuj1isPF6HHg.
Android Studio Tutorial For Beginners -2 | Android Development Tutorial | And...Edureka!
This Android Studio tutorial will help you learn the basics of Android App development. It is ideal for both beginners and professionals who wants to learn or brush up the basics of Android. This android tutorial is a two part session, and this is the second session where following topics have been discussed:
1. Event Listeners
2. Intents
YouTube Link: https://youtu.be/aGu0fbkHhek
** Data Science Master Program: https://www.edureka.co/masters-program/data-scientist-certification **
This Edureka PPT on "Data Science Full Course" provides an end to end, detailed and comprehensive knowledge on Data Science. This Data Science PPT will start with basics of Statistics and Probability and then moves to Machine Learning and Finally ends the journey with Deep Learning and AI. For Data-sets and Codes discussed in this PPT, drop a comment.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
What Is Data Science? | Introduction to Data Science | Data Science For Begin...Simplilearn
This Data Science Presentation will help you in understanding what is Data Science, why we need Data Science, prerequisites for learning Data Science, what does a Data Scientist do, Data Science lifecycle with an example and career opportunities in Data Science domain. You will also learn the differences between Data Science and Business intelligence. The role of a data scientist is one of the sexiest jobs of the century. The demand for data scientists is high, and the number of opportunities for certified data scientists is increasing. Every day, companies are looking out for more and more skilled data scientists and studies show that there is expected to be a continued shortfall in qualified candidates to fill the roles. So, let us dive deep into Data Science and understand what is Data Science all about.
This Data Science Presentation will cover the following topics:
1. Need for Data Science?
2. What is Data Science?
3. Data Science vs Business intelligence
4. Prerequisites for learning Data Science
5. What does a Data scientist do?
6. Data Science life cycle with use case
7. Demand for Data scientists
This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course.
Why learn Data Science?
Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. Data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data.
The Data Science with python is recommended for:
1. Analytics professionals who want to work with Python
2. Software professionals looking to get into the field of analytics
3. IT professionals interested in pursuing a career in analytics
4. Graduates looking to build a career in analytics and data science
5. Experienced professionals who would like to harness data science in their fields
Introduction to various data science. From the very beginning of data science idea, to latest designs, changing trends, technologies what make then to the application that are already in real world use as we of now.
In this presentation, I have talked about Big Data and its importance in brief. I have included the very basics of Data Science and its importance in the present day, through a case study. You can also get an idea about who a data scientist is and what all tasks he performs. A few applications of data science have been illustrated in the end.
How to Become a Data Analyst? | Data Analyst Skills | Data Analyst Training |...Edureka!
** Data Analytics Masters' Program: https://www.edureka.co/masters-program/data-analyst-certification **
This Edureka PPT on "How to become a data analyst" will provide you with a crisp knowledge of who a data analyst is and what are the roles and responsibilities of a data analyst. The salary trends and the companies hiring Data Analyst.
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Data Science With Python | Python For Data Science | Python Data Science Cour...Simplilearn
This Data Science with Python presentation will help you understand what is Data Science, basics of Python for data analysis, why learn Python, how to install Python, Python libraries for data analysis, exploratory analysis using Pandas, introduction to series and dataframe, loan prediction problem, data wrangling using Pandas, building a predictive model using Scikit-Learn and implementing logistic regression model using Python. The aim of this video is to provide a comprehensive knowledge to beginners who are new to Python for data analysis. This video provides a comprehensive overview of basic concepts that you need to learn to use Python for data analysis. Now, let us understand how Python is used in Data Science for data analysis.
This Data Science with Python presentation will cover the following topics:
1. What is Data Science?
2. Basics of Python for data analysis
- Why learn Python?
- How to install Python?
3. Python libraries for data analysis
4. Exploratory analysis using Pandas
- Introduction to series and dataframe
- Loan prediction problem
5. Data wrangling using Pandas
6. Building a predictive model using Scikit-learn
- Logistic regression
This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you'll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course.
Why learn Data Science?
Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. Data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data.
You can gain in-depth knowledge of Data Science by taking our Data Science with python certification training course. With Simplilearn Data Science certification training course, you will prepare for a career as a Data Scientist as you master all the concepts and techniques.
Learn more at: https://www.simplilearn.com
The presentation is about the career path in the field of Data Science. Data Science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data.
Data Science Training | Data Science For Beginners | Data Science With Python...Simplilearn
This Data Science presentation will help you understand what is Data Science, who is a Data Scientist, what does a Data Scientist do and also how Python is used for Data Science. Data science is an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining. This Data Science tutorial will help you establish your skills at analytical techniques using Python. With this Data Science video, you’ll learn the essential concepts of Data Science with Python programming and also understand how data acquisition, data preparation, data mining, model building & testing, data visualization is done. This Data Science tutorial is ideal for beginners who aspire to become a Data Scientist.
This Data Science presentation will cover the following topics:
1. What is Data Science?
2. Who is a Data Scientist?
3. What does a Data Scientist do?
This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course.
Why learn Data Science?
Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. A data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data.
You can gain in-depth knowledge of Data Science by taking our Data Science with python certification training course. With Simplilearn’s Data Science certification training course, you will prepare for a career as a Data Scientist as you master all the concepts and techniques. Those who complete the course will be able to:
1. Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics.
Install the required Python environment and other auxiliary tools and libraries
2. Understand the essential concepts of Python programming such as data types, tuples, lists, dicts, basic operators and functions
3. Perform high-level mathematical computing using the NumPy package and its largelibrary of mathematical functions.
Learn more at: https://www.simplilearn.com
This video includes:
Purpose of Data Science, Role of Data Scientist, Skills required for Data Scientist, Job roles for Data Scientist, Applications of Data Science, Career in Data Science.
Data Science is a wonderful technology that has applications in almost every field. Let's learn the basics of this domain on 16th March at (time).
Agenda
1. What is Data Science? How is it different from ML, DL, and AI
2. Why is this skill in demand?
3. What are some popular applications of Data Science
4. Popular tools and frameworks used in Data Science
My presentation at The Richmond Data Science Community (Jan 2018). The slides are slightly different than what I had presented last year at The Data Intelligence Conference.
This Angular 4 tutorial will introduce you to angular 4 components.
To watch the YouTube videos in this Angular 4 tutorial playlist, click here: https://www.youtube.com/watch?v=R4wGCHzn6-Q&list=PL9ooVrP1hQOF4aDuqaWYWSuj1isPF6HHg.
Android Studio Tutorial For Beginners -2 | Android Development Tutorial | And...Edureka!
This Android Studio tutorial will help you learn the basics of Android App development. It is ideal for both beginners and professionals who wants to learn or brush up the basics of Android. This android tutorial is a two part session, and this is the second session where following topics have been discussed:
1. Event Listeners
2. Intents
This is the first tutorial in this Angular for beginners series by Edureka. It will introduce you to angular and it's features along with the entire road map of this free Angular 4 Tutorial course.
In this tutorial, you will learn about Docker Compose and how it can be used for containerizing a MEAN stack application. Below are the topics covered in this session:
1. What Is Docker?
2. What Is Docker Compose?
3. What Is MEAN Stack?
4. Demo: Containerizing A Mean Stack App Using Docker Compose
Selenium Page Object Model Using Page Factory | Selenium Tutorial For Beginne...Edureka!
This tutorial on Selenium will help you understand what is Page Object Model (POM) and Page Factory? You will also understand why POM design pattern should be followed for creating your test case.
The following topics will be covered in this session:
1. Why Use Page Object Model(POM)?
2. What Is Page Object Model?
3. What Is Page Factory?
4. Demo: Creating POM & Page Factory
Docker Swarm For High Availability | Docker Tutorial | DevOps Tutorial | EdurekaEdureka!
In this YouTube live session, you will learn what is Docker Swarm and how Docker Swarm enables high availability of the containerized web services.
The following topics have been covered in the session:
1. What is a Docker container?
2. What is Docker Swarm?
3. Docker Swarm commands
Artificial Neural Network Tutorial | Deep Learning With Neural Networks | Edu...Edureka!
This Edureka "Neural Network Tutorial" tutorial will help you to understand the basics of Neural Networks and how to use it for deep learning. It explains Single layer and Multi layer Perceptron in detail.
Below are the topics covered in this tutorial:
1. Why Neural Networks?
2. Motivation Behind Neural Networks
3. What is Neural Network?
4. Single Layer Percpetron
5. Multi Layer Perceptron
6. Use-Case
7. Applications of Neural Networks
What Is DevOps? | Introduction To DevOps | DevOps Tools | DevOps Tutorial | D...Edureka!
In this Edureka Devops tutorial, you will learn what is DevOps, and why it is the most efficient software development methodology today. The following topics have been covered in this tutorial:
1. Software Development Challenges
2. How Does DevOps Minimize Challenges?
3. DevOps Tools & Techniques
4. Demand For DevOps Engineers
Big Data Use Cases | Hadoop Tutorial for Beginners | Hadoop Training | EdurekaEdureka!
In this Edureka tutorial, we will take you through the most popular Big Data Use-Cases like:
1. NetFlix reccommendations
2. TripAdvisor Reviews
3. ISIS Tweet Analysis
Bitcoin Blockchain Explained | Understanding Bitcoin and Blockchain | Blockch...Edureka!
In this Edureka tutorial, you will understand the fundamental concepts of Bitcoin and Blockchain along with a demo on Bitcoin transaction. This session helps you to learn the following topics:
1. What is Bitcoin?
2. Bitcoin Transaction
3. What is Blockchain?
4. Features of Blockchain
5. Demo: Bitcoin Transaction
Power BI Training | Getting Started with Power BI | Power BI Tutorial | Power...Edureka!
This Edureka tutorial on "Getting started with Power BI" will provide you the fundamental knowledge of Power BI. Below are the topics covered in this tutorial:
1. What is Self Service Business Intelligence?
2. Why Power BI?
3. What is Power BI?
4. Demo on Power BI
Django Rest Framework | How to Create a RESTful API Using Django | Django Tut...Edureka!
This Edureka “Django Rest Framework tutorial" introduces you to the concepts of API and will help you build a successful REST API in Django. This video helps you to learn the following topics:
1. What is an API?
2. Introduction to Rest Framework
3. What is Rest API?
4. Demo - Create a RESTful Web APi
Introduction To TensorFlow | Deep Learning Using TensorFlow | TensorFlow Tuto...Edureka!
In this TensorFlow tutorial, you will be learning all the basics of TensorFlow and how to create a Deep Learning Model. It includes the following topics:
1. Deep Learning vs Machine Learning
2. What is TensorFlow?
3. TensorFlow Use-Case
Angular 4 Data Binding | Two Way Data Binding in Angular 4 | Angular 4 Tutori...Edureka!
This Angular 4 tutorial will introduce you to the Angular Data Binding concept.
To watch the YouTube videos in this Angular 4 tutorial playlist, click here: https://www.youtube.com/watch?v=R4wGCHzn6-Q&list=PL9ooVrP1hQOF4aDuqaWYWSuj1isPF6HHg.
Cloud Computing Tutorial For Beginners | What is Cloud Computing | AWS Traini...Edureka!
This Cloud Computing tutorial will explain from scratch what cloud computing is all about. Towards the end, we will see how we can launch our first server on the cloud using AWS and Azure. You will learn the following topics in this tutorial:
1. Why Cloud Computing?
2. What is Cloud Computing?
3. Cloud Models
4. Cloud providers
5. Hands-on in AWS & Azure
Azure Interview Questions And Answers | Azure Tutorial For Beginners | Azure ...Edureka!
In this Azure Interview Questions and Answers tutorial, you shall get a mock on the kind of questions which you may face in your interviews on Microsoft Azure, the concepts explained here are essential for any Solution Architect in the making.
In this Azure Interview Questions tutorial, you will see questions related to:
1. General Cloud Questions
2. Introductory Azure Questions
3. Azure Interview Questions
React Components Lifecycle | React Tutorial for Beginners | ReactJS Training ...Edureka!
This Edureka tutorial on React Components will help you in understanding the fundamentals of components in ReactJS. This tutorial helps you learn the following topics:
1. React Components
2. Props
3. State
4. Flow Of Stateless & Stateful Component
5. Lifecycle Of Component
Machine Learning In Python | Python Machine Learning Tutorial | Deep Learning...Edureka!
In this Edureka "Machine Learning" tutorial, we will be covering all the fundamentals of Machine Learning.
Below are the topics covered in this tutorial:
1. What is Machine Learning?
2. Machine Learning Applications
3. Types Of Machine Learning
4. Use-Case Demo
ReactJS Tutorial For Beginners | ReactJS Redux Training For Beginners | React...Edureka!
This Edureka ReactJS Tutorial For Beginners will help you in understanding the fundamentals of ReactJS and help you in building a strong foundation in React framework. Below are the topics covered in this tutorial:
1. Why ReactJS?
2. What Is ReactJS?
3. Advantages Of ReactJS
4. ReactJS Installation and Program
5. ReactJS Fundamentals
Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...Edureka!
This Edureka Big Data tutorial helps you to understand Big Data in detail. This tutorial will be discussing about evolution of Big Data, factors associated with Big Data, different opportunities in Big Data. Further it will discuss about problems associated with Big Data and how Hadoop emerged as a solution. Below are the topics covered in this tutorial:
1) Evolution of Data
2) What is Big Data?
3) Big Data as an Opportunity
4) Problems in Encasing Big Data Opportunity
5) Hadoop as a Solution
6) Hadoop Ecosystem
7) Edureka Big Data & Hadoop Training
How to Become a Data Scientist | Data Scientist Skills | Data Science Trainin...Edureka!
** Data Science Master's Program: https://www.edureka.co/masters-program/data-scientist-certification **
This video on "How to become a Data Scientist" includes all the skills required for becoming a modern day Data Scientist. This video will answer the below questions:
1. Why should you go for data science?
2. What is the roadmap to become a data scientist?
3. What are the tools and techniques required to become a data scientist?
4. What are the roles of a data scientist?
Subscribe to our channel to get video updates. Hit the subscribe button above and click on the bell icon.
Check out our Data Science Training Playlist: https://goo.gl/Jg1pJJ
A Practical-ish Introduction to Data ScienceMark West
In this talk I will share insights and knowledge that I have gained from building up a Data Science department from scratch. This talk will be split into three sections:
1. I'll begin by defining what Data Science is, how it is related to Machine Learning and share some tips for introducing Data Science to your organisation.
2. Next up well run through some commonly used Machine Learning algorithms used by Data Scientists, along with examples for use cases where these algorithms can be applied.
3. The final third of the talk will be a demonstration of how you can quickly get started with Data Science and Machine Learning using Python and the Open Source scikit-learn Library.
Highlights and summary of long-running programmatic research on data science; practices, roles, tools, skills, organization models, workflow, outlook, etc. Profiles and persona definition for data scientist model. Landscape of org models for data science and drivers for capability planning. Secondary research materials.
Three Cool Things You Can Do with StandardsMatt Turner
Standards organizations deliver some of the world's most critical information to ensure interoperability and safety across every industry.
I gave this talk at the Standards Technology and Business Forum and covered what people are doing today and how standards organizations can
1) Better Deliver What Customers Want
2) Connect Standards to Their Customer's Data
3) Deliver Standards as Data
** Data Science Certification using R: https://www.edureka.co/data-science **
This Edureka PPT on "Predictive Analytics Using R", will help you learn about how predictive analytics works and how it can be implemented using R to solve real-world problems. Below are the topics covered in this module:
What is Predictive Analytics?
Stages of Predictive Analytics
Predictive Analytics Using R
Predictive Analytics Use case
Demo
Blog Series: http://bit.ly/data-science-blogs
Data Science Training Playlist: http://bit.ly/data-science-playlist
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GeeCon Prague 2018 - A Practical-ish Introduction to Data ScienceMark West
Data Science has been described as the sexiest job of the 21st Century. But what is Data Science? And what has Machine Learning got to do with all this? In this session I will share insights and knowledge that I have gained from building up a Data Science department from scratch. The talk will be split into three sections:
1. I’ll begin by defining what Data Science is, how it is related to Machine Learning and share some tips for introducing Data Science to your organization.
2. Next up we’ll run through some commonly used Machine Learning algorithms used by Data Scientists, along with examples for use cases where these algorithms can be applied.
3. The final third of the talk will be a demonstration of how you can quickly get started with Data Science and Machine Learning using Python and the Open Source scikit-learn Library.
TechWise with Eric Kavanagh, Dr. Robin Bloor and Dr. Kirk Borne
Live Webcast on July 23, 2014
Watch the archive: https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=59d50a520542ee7ed00a0c38e8319b54
Analytical applications are everywhere these days, and for good reason. Organizations large and small are using analytics to better understand any aspect of their business: customers, processes, behaviors, even competitors. There are several critical success factors for using analytics effectively: 1) know which kind of apps make sense for your company; 2) figure out which data sets you can use, both internal and external; 3) determine optimal roles and responsibilities for your team; 4) identify where you need help, either by hiring new employees or using consultants 5) manage your program effectively over time.
Register for this episode of TechWise to learn from two of the most experienced analysts in the business: Dr. Robin Bloor, Chief Analyst of The Bloor Group, and Dr. Kirk Borne, Data Scientist, George Mason University. Each will provide their perspective on how companies can address each of the key success factors in building, refining and using analytics to improve their business. There will then be an extensive Q&A session in which attendees can ask detailed questions of our experts and get answers in real time. Registrants will also receive a consolidated deck of slides, not just from the main presenters, but also from a variety of software vendors who provide targeted solutions.
Visit InsideAnlaysis.com for more information.
ADV Slides: What the Aspiring or New Data Scientist Needs to Know About the E...DATAVERSITY
Many data scientists are well grounded in creating accomplishment in the enterprise, but many come from outside – from academia, from PhD programs and research. They have the necessary technical skills, but it doesn’t count until their product gets to production and in use. The speaker recently helped a struggling data scientist understand his organization and how to create success in it. That turned into this presentation, because many new data scientists struggle with the complexities of an enterprise.
Data analytics has grown beyond being a mere business tool; it is now a driving force behind technological advancements and a cornerstone of competitiveness across diverse industries. Whether you are a budding data analyst or a seasoned professional, the ever-evolving world of Data Analytics Training Course in Noida offers a dynamic and promising path for those who seek to explore, understand, and harness the incredible potential of data. As data continues to shape our future, embracing the principles of data analytics is not merely an option but a necessity for anyone aspiring to thrive in the digital age.
https://aptronsolutions.com/best-data-analytics-training-in-noida.html
JavaZone 2018 - A Practical(ish) Introduction to Data ScienceMark West
Code: https://github.com/markwest1972/titanic
Video: https://vimeo.com/289705893
Data Science has been described as the sexiest job of the 21st Century. But what is Data Science? And what has Machine Learning got to do with all of this?
In this talk I will share insights and knowledge that I have gained from building up a Data Science department from scratch. This talk will be split into three sections:
1. I’ll begin by defining what Data Science is, how it is related to Machine Learning and share some tips for introducing Data Science to your organisation.
2. Next up we’ll run through some commonly used Machine Learning algorithms used by Data Scientists, along with examples for use cases where these algorithms can be applied.
3. The final third of the talk will be a demonstration of how you can quickly get started with Data Science and Machine Learning using Python and the Open Source scikit-learn Library.
Analytics thought-leader Thomas Davenport and leading industry experts discuss how—and why—organizations like yours use business analytics to empower more timely and precise decisions by bringing new insights into daily operations.
Similar to What Is Data Science? Data Science Course - Data Science Tutorial For Beginners | Edureka (20)
What to learn during the 21 days Lockdown | EdurekaEdureka!
Register Here: https://resources.edureka.co/21-days-learning-plan-webinar/
In light of the complete national lockdown for 21 days, we invite you to join a FREE webinar by renowned Mentor and Advisor, Nitin Gupta as he helps you create a 21-day learning gameplan to maximize returns for your career.
The webinar will help freshers and experienced professionals to capitalize on these 21 days and figure out the best technologies to learn while confined to home.
You will also get all your questions and doubts resolved in real-time.
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Top 10 Dying Programming Languages in 2020 | EdurekaEdureka!
YouTube Link: https://youtu.be/LSM7hD6GM4M
Get Edureka Certified in Trending Programming Languages: https://www.edureka.co
In this highly competitive IT industry, everyone wants to learn programming languages that will keep them ahead of the game. But knowing what to learn so you gain the most out of your knowledge is a whole other ball game. So, we at Edureka have prepared a list of Top 10 Dying Programming Languages 2020 that will help you to make the right choice for your career. Meanwhile, if you ever wondered about which languages are slated for continuing uptake and possible greatness, we have a list for that, too.
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Top 5 Trending Business Intelligence Tools | EdurekaEdureka!
YouTube Link: https://youtu.be/eEwq_mPd1iI
Edureka BI Certification Training Courses: https://www.edureka.co/bi-and-visualization-certification-courses
Receiving insights and finding trends is absolutely critical for businesses to scale and adapt as the years go on. This is exactly what business intelligence does and the best thing about these software solutions is that their potential uses are practically unlimited.
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Tableau Tutorial for Data Science | EdurekaEdureka!
YouTube Link:https://youtu.be/ZHNdSKMluI0
Edureka Tableau Certification Training: https://www.edureka.co/tableau-certification-training
This Edureka's PPT on "Tableau for Data Science" will help you to utilize Tableau as a tool for Data Science, not only for engagement but also comprehension efficiency. Through this PPT, you will learn to gain the maximum amount of insight with the least amount of effort.
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YouTube Link:https://youtu.be/CVv8zhYEjUE
Edureka Python Certification Training: https://www.edureka.co/data-science-python-certification-course
This Edureka PPT on 'Python Programming' will help you learn Python programming basics with the help of interesting hands-on implementations.
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Get Edureka Certified in Trending Project Management Certifications: https://www.edureka.co/project-management-and-methodologies-certification-courses
Whether you want to scale up your career or are trying to switch your career path, Project Management Certifications seems to be a perfect choice in either case. So, we at Edureka have prepared a list of Top 5 Project Management Certifications that you must check out in 2020 for a major career boost.
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Top Maven Interview Questions in 2020 | EdurekaEdureka!
YouTube Link: https://youtu.be/5iTcAR4fScM
**DevOps Certification Courses - https://www.edureka.co/devops-certification-training***
This video on 'Maven Interview Questions' discusses the most frequently asked Maven Interview Questions. This PPT will help give you a detailed explanation of the topics which will help you in acing the interviews.
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** Linux Administration Certification Training - https://www.edureka.co/linux-admin **
Linux Mint is the first operating system that people from Windows or Mac are drawn towards when they have to switch to Linux in their work environment. Linux Mint has been around since the year 2006 and has grown and matured into a very user-friendly OS. Do watch the PPT till the very end to see all the demonstrations.
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How to Deploy Java Web App in AWS| EdurekaEdureka!
YouTube Link:https://youtu.be/Ozc5Yu_IcaI
** Edureka AWS Architect Certification Training - https://www.edureka.co/aws-certification-training**
This Edureka PPT shows how to deploy a java web application in AWS using AWS Elastic Beanstalk. It also describes the advantages of using AWS for this purpose.
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YouTube Link:https://youtu.be/phPCkkWT76k
*** Edureka Digital Marketing Course: https://www.edureka.co/post-graduate/digital-marketing-certification***
This Edureka PPT on "Top 10 Reasons to Learn Digital Marketing" will help you understand why you should take up Digital Marketing
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** RPA Training: https://www.edureka.co/robotic-process-automation-training**
This PPT on RPA in 2020 will provide a glimpse of the accomplishments and benefits provided by RPA. Also, it will list out the new changes and technologies that will collaborate with RPA in 2020.
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**DevOps Certification Courses - https://www.edureka.co/devops-certification-training **
This PPT shows how to configure Jenkins to receive email notifications. It also includes a demo that shows how to do it in 6 simple steps in the Windows machine.
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EA Algorithm in Machine Learning | EdurekaEdureka!
YouTube Link: https://youtu.be/DIADjJXrgps
** Machine Learning Certification Training: https://www.edureka.co/machine-learning-certification-training **
This Edureka PPT on 'EM Algorithm In Machine Learning' covers the EM algorithm along with the problem of latent variables in maximum likelihood and Gaussian mixture model.
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PGP in AI and Machine Learning (9 Months Online Program): https://www.edureka.co/post-graduate/machine-learning-and-ai
This Edureka PPT on "Cognitive AI" explains cognitive computing and how it helps in making better human decisions at work. Also, it explains the differences between cognitive computing and artificial intelligence.
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Edureka AWS Architect Certification Training - https://www.edureka.co/aws-certification-training
This Edureka PPT on AWS Cloud Practitioner will provide a complete guide to your AWS Cloud Practitioner Certification exam. It will explain the exam details, objectives, why you should get certified and also how AWS certification will help your career.
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Blue Prism Top Interview Questions | EdurekaEdureka!
YouTube Link: https://youtu.be/ykbRdUNIbyQ
** RPA Training: https://www.edureka.co/robotic-process-automation-certification-courses**
This PPT on Blue Prism Interview Questions will cover the Top 50 Blue Prism related questions asked in your interviews.
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AWS Architect Certification Training: https://www.edureka.co/aws-certification-training
This PPT will help you in understanding how AWS deals smartly with Big Data. It also shows how AWS can solve Big Data challenges with ease.
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A star algorithm | A* Algorithm in Artificial Intelligence | EdurekaEdureka!
YouTube Link: https://youtu.be/amlkE0g-YFU
** Artificial Intelligence and Deep Learning: https://www.edureka.co/ai-deep-learni... **
This Edureka PPT on 'A Star Algorithm' teaches you all about the A star Algorithm, the uses, advantages and disadvantages and much more. It also shows you how the algorithm can be implemented practically and has a comparison between the Dijkstra and itself.
Check out our playlist for more videos: http://bit.ly/2taym8X
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Kubernetes Installation on Ubuntu | EdurekaEdureka!
YouTube Link: https://youtu.be/UWg3ORRRF60
Kubernetes Certification: https://www.edureka.co/kubernetes-certification
This Edureka PPT will help you set up a Kubernetes cluster having 1 master and 1 node. The detailed step by step instructions is demonstrated in this PPT.
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DevOps Training: https://www.edureka.co/devops-certification-training
This Edureka DevOps Tutorial for Beginners talks about What is DevOps and how it works. You will learn about several DevOps tools (Git, Jenkins, Docker, Puppet, Ansible, Nagios) involved at different DevOps stages such as version control, continuous integration, continuous delivery, continuous deployment, continuous monitoring.
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Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
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What Will You Learn Today?
What is Data Science
Need Of Data Science Use case of Data Science
Business Intelligence
vs. Data Science
Tools used in Data Science Lifecycle of Data Science
1 2 3
4 6
5
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Need Of Data Science
Revolution
of
Technology
Unstructured Data
Data Storage
Lack of scientific
insights
Data Science
Prediction
Decision making
Pattern discovery
Data Flow
Lack of predictive
analytics
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Need Of Data Science
You can use Data Science to
Recommend the right product to the right customer to
enhance business.
Predict the characteristics of high LTV customers and
helps in customer segmentation.
Build intelligence and ability in machines.
Predict fraudulent transactions beforehand.
Perform sentiment analysis to predict the outcome
of elections.
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What Is Data Science?
Data Science is a blend of various tools,
algorithms, and machine learning principles with
the goal to discover hidden patterns from the raw
data.
Data Science is primarily used to make decisions
and predictions.
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What Is Data Science?
Basketball teams are using data for tracking team
strategies and outcome of matches.
Below parameters will be used for model building.
• Average pass time of ball.
• Number of successful passes.
• Speed and accuracy of successful baskets.
• Area of court the player on average is
shadowing.
Models built on the basis of data science algorithms
help in pattern discovery of player game.
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What Is Data Science?
Amazon has huge amount of consumer purchasing
data.
The data consists of consumer demographics (age,
sex, location), purchasing history, past browsing
history.
Based on this data, Amazon segments its
customers, draws a pattern and recommends the
right product to the right customer at the right
time.
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What Is Data Science?
Google self driving car is a smart, driverless car.
It collects data from environment through
sensors.
Takes decisions like when to speed up, when to
speed down, when to overtake and when to turn.
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Role Of A Data Scientist
The Data Scientist will be responsible for designing and creating processes and layouts for complex, large-
scale data sets used for modeling, data mining, and research purposes.
Responsibilities
Selecting features, building and optimizing classifiers using machine learning techniques.
Data mining using state-of-the-art methods.
Extending company’s data with third party sources of information when needed.
Processing, cleansing, and verifying the integrity of data for analysis.
Building predictive models using Machine Learning algorithms.
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BI Vs. Data Science
Characteristics Business Intelligence Data Science
Perspective Looking Backward Looking Forward
Data Sources
Structured
(Usually SQL, often Data Warehouse)
Both Structured and Unstructured
( logs, cloud data, SQL, NoSQL, text)
Approach Statistics and Visualization
Statistics, Machine Learning, Graph
Analysis, Neuro- linguistic Programming
(NLP)
Focus Past and Present Present and Future
Tools Pentaho, Microsoft BI, QlikView, R RapidMiner, BigML, Weka, R
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Tools Used In Data Science
Data analysis Data warehousing Data visualization Machine learning
• R
• Spark
• Python
• SAS
• Hadoop
• SQL
• Hive
• R
• Tableau
• Raw
• Spark
• Mahout
• Azure ML studio
Commonly used tools by Data Scientists
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What if we could predict the
occurrence of diabetes and
take appropriate measures
beforehand to prevent it?
Definitely! Let me take you
through the steps to
predict the vulnerable
patients.
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Lifecycle Of Data Science
Discovery
Data Preparation
Model Planning
Model Building
Operationalize
Communicate Results
Discovery involves acquiring data from all the identified internal and
external sources that can help answer the business question.
This data could be
• logs from webservers
• social media data
• census datasets
• data streamed from online sources via APIs
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Lifecycle Of Data Science
Discovery
Data Preparation
Model Planning
Model Building
Operationalize
Communicate Results
Doctor gets this data from the medical
history of the patient.
Attributes:
npreg – Number of times pregnant
glucose – Plasma glucose concentration
bp – Blood pressure
skin – Triceps skinfold thickness
bmi – Body mass index
ped – Diabetes pedigree function
age – Age
income – Income
Income is an irrelevant attribute in the
prediction of diabetes
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Discovery
Data Preparation
Model Planning
Model Building
Operationalize
Communicate Results
The data can have a lot of inconsistencies like missing values, blank
columns, abrupt values and incorrect data format which need to be
cleaned.
It is required to explore, preprocess and condition data prior to modeling.
This will help you to spot the outliers and establish a relationship between
the variables.
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Discovery
Data Preparation
Model Planning
Model Building
Operationalize
Communicate Results
This data has lot of anomalies and needs cleansing before further
analysis can be done.
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Discovery
Data Preparation
Model Planning
Model Building
Operationalize
Communicate Results
We clean and preprocess this data by removing the outliers, filling up the
null values and normalizing the data type.
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Lifecycle Of Data Science
Discovery
Data Preparation
Model Planning
Model Building
Operationalize
Communicate Results
Here, we determine the methods and techniques to draw the relationships
between variable.
Apply Exploratory Data Analytics (EDA) using various statistical formulas and
visualization tools.
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Lifecycle Of Data Science
Discovery
Data Preparation
Model Planning
Model Building
Operationalize
Communicate Results
Use of visualization techniques like histograms, line graphs, box plots to get a fair
idea of the distribution of data.
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Lifecycle Of Data Science
Discovery
Data Preparation
Model Planning
Model Building
Operationalize
Communicate Results
Develop datasets for training and testing purposes.
Consider whether existing tools will suffice for running the models.
Analyze various learning techniques like classification, association and
clustering to build the model.
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Lifecycle Of Data Science
Discovery
Data Preparation
Model Planning
Model Building
Operationalize
Communicate Results
This is a decision tree based on different attributes.
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Lifecycle Of Data Science
Discovery
Data Preparation
Model Planning
Model Building
Operationalize
Communicate Results
Deliver final reports, briefings, code and technical documents.
Implement pilot project in a real-time production environment.
Look for performance constraints if any.
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Lifecycle Of Data Science
Discovery
Initialization
Model Planning
Model Building
Deployment
Communicate Results
Identify all the key findings and communicate to the stakeholders.
Explaining the model and result to medical authorities.
Determine if the results of the project are a success or a failure based on the
criteria developed.
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Lifecycle Of Data Science
Discovery
Initialization
Model Planning
Model Building
Deployment
Communicate Results
Diabetes Positive set:
• glucose > 154
• glucose >127 & <= 154 + bmi >30.9
• glucose<=127 + pregnant >5
• glucose<=127 + pregnant <=5 + age >28
• glucose<=127 + pregnant <=5 + age <=28 +bmi > 30.9
Diabetes Negative set:
• glucose > 154
• glucose >127 & <= 154 + bmi <=30.9
• glucose<=127 + pregnant <=5 + age <=28 +bmi <= 30.9
We can use this decision tree result to know whether the patient is
vulnerable to diabetes or not.
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Course Details
Go to www.edureka.co/data-science
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